Sellers, K F and Shmueli, G
(2013)
Data dispersion: Now you see it. now you don't.
Communications in Statistics - Theory and Methods, 42 (17).
pp. 3134-3137.
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Abstract
Poisson regression is the most well-known method for modeling count data. When data display over-dispersion, thereby violating the underlying equi-dispersion assumption of Poisson regression, the common solution is to use negative-binomial regression. We show, however, that count data that appear to be equi-or over-dispersed may actually stem from a mixture of populations with different dispersion levels. To detect and model such a mixture, we introduce a generalization of the Conway-Maxwell-Poisson (COM-Poisson) regression model that allows for group-level dispersion. We illustrate mixed dispersion effects and the proposed methodology via semi-authentic data. © 2013 Taylor and Francis Group, LLC.
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